blob: dccbe4045d27bece722cd6cbfc46998b2b318ca0 [file] [log] [blame]
/*
* Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "arm_compute/runtime/CPP/functions/CPPBoxWithNonMaximaSuppressionLimit.h"
#include "arm_compute/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.h"
#include "arm_compute/runtime/Scheduler.h"
#include "src/common/utils/Log.h"
namespace arm_compute
{
namespace
{
void dequantize_tensor(const ITensor *input, ITensor *output)
{
const UniformQuantizationInfo qinfo = input->info()->quantization_info().uniform();
const DataType data_type = input->info()->data_type();
Window window;
window.use_tensor_dimensions(input->info()->tensor_shape());
Iterator input_it(input, window);
Iterator output_it(output, window);
switch(data_type)
{
case DataType::QASYMM8:
execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<float *>(output_it.ptr()) = dequantize(*reinterpret_cast<const uint8_t *>(input_it.ptr()), qinfo.scale, qinfo.offset);
},
input_it, output_it);
break;
case DataType::QASYMM8_SIGNED:
execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<float *>(output_it.ptr()) = dequantize_qasymm8_signed(*reinterpret_cast<const int8_t *>(input_it.ptr()), qinfo);
},
input_it, output_it);
break;
case DataType::QASYMM16:
execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<float *>(output_it.ptr()) = dequantize(*reinterpret_cast<const uint16_t *>(input_it.ptr()), qinfo.scale, qinfo.offset);
},
input_it, output_it);
break;
default:
ARM_COMPUTE_ERROR("Unsupported data type");
}
}
void quantize_tensor(const ITensor *input, ITensor *output)
{
const UniformQuantizationInfo qinfo = output->info()->quantization_info().uniform();
const DataType data_type = output->info()->data_type();
Window window;
window.use_tensor_dimensions(input->info()->tensor_shape());
Iterator input_it(input, window);
Iterator output_it(output, window);
switch(data_type)
{
case DataType::QASYMM8:
execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<uint8_t *>(output_it.ptr()) = quantize_qasymm8(*reinterpret_cast<const float *>(input_it.ptr()), qinfo);
},
input_it, output_it);
break;
case DataType::QASYMM8_SIGNED:
execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<int8_t *>(output_it.ptr()) = quantize_qasymm8_signed(*reinterpret_cast<const float *>(input_it.ptr()), qinfo);
},
input_it, output_it);
break;
case DataType::QASYMM16:
execute_window_loop(window, [&](const Coordinates &)
{
*reinterpret_cast<uint16_t *>(output_it.ptr()) = quantize_qasymm16(*reinterpret_cast<const float *>(input_it.ptr()), qinfo);
},
input_it, output_it);
break;
default:
ARM_COMPUTE_ERROR("Unsupported data type");
}
}
} // namespace
CPPBoxWithNonMaximaSuppressionLimit::CPPBoxWithNonMaximaSuppressionLimit(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(std::move(memory_manager)),
_box_with_nms_limit_kernel(),
_scores_in(),
_boxes_in(),
_batch_splits_in(),
_scores_out(),
_boxes_out(),
_classes(),
_batch_splits_out(),
_keeps(),
_scores_in_f32(),
_boxes_in_f32(),
_batch_splits_in_f32(),
_scores_out_f32(),
_boxes_out_f32(),
_classes_f32(),
_batch_splits_out_f32(),
_keeps_f32(),
_is_qasymm8(false)
{
}
void CPPBoxWithNonMaximaSuppressionLimit::configure(const ITensor *scores_in, const ITensor *boxes_in, const ITensor *batch_splits_in,
ITensor *scores_out, ITensor *boxes_out, ITensor *classes, ITensor *batch_splits_out,
ITensor *keeps, ITensor *keeps_size, const BoxNMSLimitInfo info)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(scores_in, boxes_in, scores_out, boxes_out, classes);
ARM_COMPUTE_LOG_PARAMS(scores_in, boxes_in, batch_splits_in, scores_out, boxes_out, classes, batch_splits_out, keeps, keeps_size, info);
_is_qasymm8 = scores_in->info()->data_type() == DataType::QASYMM8 || scores_in->info()->data_type() == DataType::QASYMM8_SIGNED;
_scores_in = scores_in;
_boxes_in = boxes_in;
_batch_splits_in = batch_splits_in;
_scores_out = scores_out;
_boxes_out = boxes_out;
_classes = classes;
_batch_splits_out = batch_splits_out;
_keeps = keeps;
if(_is_qasymm8)
{
// Manage intermediate buffers
_memory_group.manage(&_scores_in_f32);
_memory_group.manage(&_boxes_in_f32);
_memory_group.manage(&_scores_out_f32);
_memory_group.manage(&_boxes_out_f32);
_memory_group.manage(&_classes_f32);
_scores_in_f32.allocator()->init(scores_in->info()->clone()->set_data_type(DataType::F32));
_boxes_in_f32.allocator()->init(boxes_in->info()->clone()->set_data_type(DataType::F32));
if(batch_splits_in != nullptr)
{
_memory_group.manage(&_batch_splits_in_f32);
_batch_splits_in_f32.allocator()->init(batch_splits_in->info()->clone()->set_data_type(DataType::F32));
}
_scores_out_f32.allocator()->init(scores_out->info()->clone()->set_data_type(DataType::F32));
_boxes_out_f32.allocator()->init(boxes_out->info()->clone()->set_data_type(DataType::F32));
_classes_f32.allocator()->init(classes->info()->clone()->set_data_type(DataType::F32));
if(batch_splits_out != nullptr)
{
_memory_group.manage(&_batch_splits_out_f32);
_batch_splits_out_f32.allocator()->init(batch_splits_out->info()->clone()->set_data_type(DataType::F32));
}
if(keeps != nullptr)
{
_memory_group.manage(&_keeps_f32);
_keeps_f32.allocator()->init(keeps->info()->clone()->set_data_type(DataType::F32));
}
_box_with_nms_limit_kernel.configure(&_scores_in_f32, &_boxes_in_f32, (batch_splits_in != nullptr) ? &_batch_splits_in_f32 : nullptr,
&_scores_out_f32, &_boxes_out_f32, &_classes_f32,
(batch_splits_out != nullptr) ? &_batch_splits_out_f32 : nullptr, (keeps != nullptr) ? &_keeps_f32 : nullptr,
keeps_size, info);
}
else
{
_box_with_nms_limit_kernel.configure(scores_in, boxes_in, batch_splits_in, scores_out, boxes_out, classes, batch_splits_out, keeps, keeps_size, info);
}
if(_is_qasymm8)
{
_scores_in_f32.allocator()->allocate();
_boxes_in_f32.allocator()->allocate();
if(_batch_splits_in != nullptr)
{
_batch_splits_in_f32.allocator()->allocate();
}
_scores_out_f32.allocator()->allocate();
_boxes_out_f32.allocator()->allocate();
_classes_f32.allocator()->allocate();
if(batch_splits_out != nullptr)
{
_batch_splits_out_f32.allocator()->allocate();
}
if(keeps != nullptr)
{
_keeps_f32.allocator()->allocate();
}
}
}
Status validate(const ITensorInfo *scores_in, const ITensorInfo *boxes_in, const ITensorInfo *batch_splits_in, const ITensorInfo *scores_out, const ITensorInfo *boxes_out, const ITensorInfo *classes,
const ITensorInfo *batch_splits_out, const ITensorInfo *keeps, const ITensorInfo *keeps_size, const BoxNMSLimitInfo info)
{
ARM_COMPUTE_UNUSED(batch_splits_in, batch_splits_out, keeps, keeps_size, info);
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(scores_in, boxes_in, scores_out, boxes_out, classes);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(scores_in, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32);
const bool is_qasymm8 = scores_in->data_type() == DataType::QASYMM8 || scores_in->data_type() == DataType::QASYMM8_SIGNED;
if(is_qasymm8)
{
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(boxes_in, 1, DataType::QASYMM16);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(boxes_in, boxes_out);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(boxes_in, boxes_out);
const UniformQuantizationInfo boxes_qinfo = boxes_in->quantization_info().uniform();
ARM_COMPUTE_RETURN_ERROR_ON(boxes_qinfo.scale != 0.125f);
ARM_COMPUTE_RETURN_ERROR_ON(boxes_qinfo.offset != 0);
}
return Status{};
}
void CPPBoxWithNonMaximaSuppressionLimit::run()
{
// Acquire all the temporaries
MemoryGroupResourceScope scope_mg(_memory_group);
if(_is_qasymm8)
{
dequantize_tensor(_scores_in, &_scores_in_f32);
dequantize_tensor(_boxes_in, &_boxes_in_f32);
if(_batch_splits_in != nullptr)
{
dequantize_tensor(_batch_splits_in, &_batch_splits_in_f32);
}
}
Scheduler::get().schedule(&_box_with_nms_limit_kernel, Window::DimY);
if(_is_qasymm8)
{
quantize_tensor(&_scores_out_f32, _scores_out);
quantize_tensor(&_boxes_out_f32, _boxes_out);
quantize_tensor(&_classes_f32, _classes);
if(_batch_splits_out != nullptr)
{
quantize_tensor(&_batch_splits_out_f32, _batch_splits_out);
}
if(_keeps != nullptr)
{
quantize_tensor(&_keeps_f32, _keeps);
}
}
}
} // namespace arm_compute